Public reimbursement policies in Canada for direct-acting antiviral treatment of hepatitis C virus infection: A descriptive study
Bibliographic record
Abstract
Background: Direct-acting antiviral (DAA) therapies have simplified HCV treatment, and publicly funded Canadian drug plans have eliminated disease-stage restrictions for reimbursement of DAA therapies. However other policies which complicate, delay, or prevent treatment initiation still persist. We aim to describe these plans' existing reimbursement criteria and appraise whether they hinder treatment access. Methods: We reviewed DAA reimbursement policies of 16 publicly funded drug plans published online and provided by contacts with in-depth knowledge of prescribing criteria. Data were collected from May to July 2022. Primary outcomes were: (1) if plans have arranged to accept point-of-care HCV RNA testing for diagnosis; testing requirements for (2) HCV genotype, (3) fibrosis stage, and (4) chronic infection; (5) time taken and method used to approve reimbursement requests; (6) providers eligible to prescribe DAAs; and (7) restrictions on re-treatment. Results: Fifteen (94%) plans have at least one policy in place which limits simplified HCV treatment. Many plans continue to require results of genotype or fibrosis staging, limit eligible prescribers, and take longer than 1 day to approve coverage requests. One plan discourages treatment for re-infection. Conclusion: Reimbursement criteria set by publicly funded Canadian drug plans continue to limit timely, equitable access to HCV treatment. Eliminating clinically irrelevant pre-authorization testing, expanding eligible prescribers, expediting claims processing, and broadening coverage of treatment for reinfection will improve access to DAAs. The federal government could further enhance efforts by introducing a federal HCV elimination strategy or federal high-cost drug PharmaCare program.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.019 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".